docs: aws docs updates (#20571)

2025-07-03 11:47:49 +00:00 · 2024-04-17 16:32:00 -07:00 · 2024-04-17 16:32:00 -07:00 · e395115807
commit e395115807
parent f09bd0b75b
9 changed files with 117 additions and 102 deletions
--- a/docs/docs/integrations/chat/bedrock.ipynb
+++ b/docs/docs/integrations/chat/bedrock.ipynb
@ -3,10 +3,14 @@
  {
   "cell_type": "raw",
   "id": "fbc66410",
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "raw"
+    }
+   },
   "source": [
    "---\n",
-    "sidebar_label: Bedrock Chat\n",
+    "sidebar_label: Bedrock\n",
    "---"
   ]
  },
@ -15,7 +19,7 @@
   "id": "bf733a38-db84-4363-89e2-de6735c37230",
   "metadata": {},
   "source": [
-    "# BedrockChat\n",
+    "# ChatBedrock\n",
    "\n",
    ">[Amazon Bedrock](https://aws.amazon.com/bedrock/) is a fully managed service that offers a choice of \n",
    "> high-performing foundation models (FMs) from leading AI companies like `AI21 Labs`, `Anthropic`, `Cohere`, \n",
@ -30,42 +34,53 @@
  },
  {
   "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
   "id": "d51edc81",
   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
   "source": [
-    "%pip install --upgrade --quiet  boto3"
+    "%pip install --upgrade --quiet  langchain-aws"
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
   "id": "d4a7c55d-b235-4ca4-a579-c90cc9570da9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
-    "from langchain_community.chat_models import BedrockChat\n",
+    "from langchain_aws import ChatBedrock\n",
    "from langchain_core.messages import HumanMessage"
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 11,
   "id": "70cf04e8-423a-4ff6-8b09-f11fb711c817",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
-    "chat = BedrockChat(model_id=\"anthropic.claude-v2\", model_kwargs={\"temperature\": 0.1})"
+    "chat = ChatBedrock(\n",
+    "    model_id=\"anthropic.claude-3-sonnet-20240229-v1:0\",\n",
+    "    model_kwargs={\"temperature\": 0.1},\n",
+    ")"
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 12,
   "id": "8199ef8f-eb8b-4253-9ea0-6c24a013ca4c",
   "metadata": {
    "tags": []
@ -74,10 +89,10 @@
    {
     "data": {
      "text/plain": [
-       "AIMessage(content=\" Voici la traduction en français : J'adore programmer.\", additional_kwargs={}, example=False)"
+       "AIMessage(content=\"Voici la traduction en français :\\n\\nJ'aime la programmation.\", additional_kwargs={'usage': {'prompt_tokens': 20, 'completion_tokens': 21, 'total_tokens': 41}}, response_metadata={'model_id': 'anthropic.claude-3-sonnet-20240229-v1:0', 'usage': {'prompt_tokens': 20, 'completion_tokens': 21, 'total_tokens': 41}}, id='run-994f0362-0e50-4524-afad-3c4f5bb11328-0')"
      ]
     },
-     "execution_count": 3,
+     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
@ -88,7 +103,7 @@
    "        content=\"Translate this sentence from English to French. I love programming.\"\n",
    "    )\n",
    "]\n",
-    "chat(messages)"
+    "chat.invoke(messages)"
   ]
  },
  {
@ -97,39 +112,30 @@
   "id": "a4a4f4d4",
   "metadata": {},
   "source": [
-    "### For BedrockChat with Streaming"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c253883f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
+    "### Streaming\n",
    "\n",
-    "chat = BedrockChat(\n",
-    "    model_id=\"anthropic.claude-v2\",\n",
-    "    streaming=True,\n",
-    "    callbacks=[StreamingStdOutCallbackHandler()],\n",
-    "    model_kwargs={\"temperature\": 0.1},\n",
-    ")"
+    "To stream responses, you can use the runnable `.stream()` method."
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
   "id": "d9e52838",
   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Voici la traduction en français :\n",
+      "\n",
+      "J'aime la programmation."
+     ]
+    }
+   ],
   "source": [
-    "messages = [\n",
-    "    HumanMessage(\n",
-    "        content=\"Translate this sentence from English to French. I love programming.\"\n",
-    "    )\n",
-    "]\n",
-    "chat(messages)"
+    "for chunk in chat.stream(messages):\n",
+    "    print(chunk.content, end=\"\", flush=True)"
   ]
  }
 ],
@ -149,7 +155,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.11.4"
  }
 },
 "nbformat": 4,
--- a/docs/docs/integrations/graphs/amazon_neptune_sparql.ipynb
+++ b/docs/docs/integrations/graphs/amazon_neptune_sparql.ipynb
@ -118,25 +118,7 @@
   "metadata": {},
   "outputs": [],
   "source": [
-    "!pip install --upgrade --force-reinstall langchain"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!pip install --upgrade --force-reinstall langchain-core"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!pip install --upgrade --force-reinstall langchain-community"
+    "!pip install --upgrade --quiet langchain langchain-community langchain-aws"
   ]
  },
  {
@ -264,7 +246,7 @@
   "source": [
    "import boto3\n",
    "from langchain.chains.graph_qa.neptune_sparql import NeptuneSparqlQAChain\n",
-    "from langchain_community.chat_models import BedrockChat\n",
+    "from langchain_aws import ChatBedrock\n",
    "from langchain_community.graphs import NeptuneRdfGraph\n",
    "\n",
    "host = \"<your host>\"\n",
@ -279,7 +261,7 @@
    "\n",
    "MODEL_ID = \"anthropic.claude-v2\"\n",
    "bedrock_client = boto3.client(\"bedrock-runtime\")\n",
-    "llm = BedrockChat(model_id=MODEL_ID, client=bedrock_client)\n",
+    "llm = ChatBedrock(model_id=MODEL_ID, client=bedrock_client)\n",
    "\n",
    "chain = NeptuneSparqlQAChain.from_llm(\n",
    "    llm=llm,\n",
--- a/docs/docs/integrations/platforms/aws.mdx
+++ b/docs/docs/integrations/platforms/aws.mdx
@ -2,6 +2,28 @@

 The `LangChain` integrations related to [Amazon AWS](https://aws.amazon.com/) platform.

+First-party AWS integrations are available in the `langchain_aws` package.
+
+```bash
+pip install langchain-aws
+```
+
+And there are also some community integrations available in the `langchain_community` package with the `boto3` optional dependency.
+
+```bash
+pip install langchain-community boto3
+```
+
+## Chat models
+
+### Bedrock Chat
+
+See a [usage example](/docs/integrations/chat/bedrock).
+
+```python
+from langchain_aws import ChatBedrock
+```
+
 ## LLMs

 ### Bedrock
@ -20,7 +42,7 @@ The `LangChain` integrations related to [Amazon AWS](https://aws.amazon.com/) pl
 See a [usage example](/docs/integrations/llms/bedrock).

 ```python
-from langchain_community.llms.bedrock import Bedrock
+from langchain_aws import BedrockLLM
 ```

 ### Amazon API Gateway
@ -53,18 +75,7 @@ We use `SageMaker` to host our model and expose it as the `SageMaker Endpoint`.
 See a [usage example](/docs/integrations/llms/sagemaker).

 ```python
-from langchain_community.llms import SagemakerEndpoint
-from langchain_community.llms.sagemaker_endpoint import LLMContentHandler
-```
-
-## Chat models
-
-### Bedrock Chat
-
-See a [usage example](/docs/integrations/chat/bedrock).
-
-```python
-from langchain_community.chat_models import BedrockChat
+from langchain_aws import SagemakerEndpoint
 ```

 ## Embedding Models
@ -188,16 +199,16 @@ from langchain.vectorstores import DocumentDBVectorSearch
 > manuals, and websites. It supports multiple languages and can understand complex queries, synonyms, and 
 > contextual meanings to provide highly relevant search results.

-We need to install the `boto3` library.
+We need to install the `langchain-aws` library.

 ```bash
-pip install boto3
+pip install langchain-aws
 ```

 See a [usage example](/docs/integrations/retrievers/amazon_kendra_retriever).

 ```python
-from langchain.retrievers import AmazonKendraRetriever
+from langchain_aws import AmazonKendraRetriever
 ```

 ### Amazon Bedrock (Knowledge Bases)
@ -206,16 +217,16 @@ from langchain.retrievers import AmazonKendraRetriever
 > `Amazon Web Services` (`AWS`) offering which lets you quickly build RAG applications by using your 
 > private data to customize foundation model response.

-We need to install the `boto3` library.
+We need to install the `langchain-aws` library.

 ```bash
-pip install boto3
+pip install langchain-aws
 ```

 See a [usage example](/docs/integrations/retrievers/bedrock).

 ```python
-from langchain.retrievers import AmazonKnowledgeBasesRetriever
+from langchain_aws import AmazonKnowledgeBasesRetriever
 ```

 ## Tools
--- a/docs/docs/modules/model_io/chat/response_metadata.ipynb
+++ b/docs/docs/modules/model_io/chat/response_metadata.ipynb
@ -158,9 +158,9 @@
    }
   ],
   "source": [
-    "from langchain_community.chat_models import BedrockChat\n",
+    "from langchain_aws import ChatBedrock\n",
    "\n",
-    "llm = BedrockChat(model_id=\"anthropic.claude-v2\")\n",
+    "llm = ChatBedrock(model_id=\"anthropic.claude-v2\")\n",
    "msg = llm.invoke([(\"human\", \"What's the oldest known example of cuneiform\")])\n",
    "msg.response_metadata"
   ]
--- a/docs/docs/modules/model_io/chat/token_usage_tracking.ipynb
+++ b/docs/docs/modules/model_io/chat/token_usage_tracking.ipynb
@ -307,7 +307,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 1,
   "id": "4a3eced5-2ff7-49a7-a48b-768af8658323",
   "metadata": {},
   "outputs": [
@ -315,33 +315,41 @@
     "name": "stdout",
     "output_type": "stream",
     "text": [
-      "Tokens Used: 79\n",
-      "\tPrompt Tokens: 26\n",
-      "\tCompletion Tokens: 53\n",
+      "Tokens Used: 0\n",
+      "\tPrompt Tokens: 0\n",
+      "\tCompletion Tokens: 0\n",
      "Successful Requests: 2\n",
-      "Total Cost (USD): $0.00148\n"
+      "Total Cost (USD): $0.0\n"
     ]
    }
   ],
   "source": [
-    "# !pip install boto3\n",
+    "# !pip install langchain-aws\n",
+    "from langchain_aws import ChatBedrock\n",
    "from langchain_community.callbacks.manager import get_bedrock_anthropic_callback\n",
-    "from langchain_community.chat_models import BedrockChat\n",
    "\n",
-    "llm = BedrockChat(model_id=\"anthropic.claude-v2\")\n",
+    "llm = ChatBedrock(model_id=\"anthropic.claude-v2\")\n",
    "\n",
    "with get_bedrock_anthropic_callback() as cb:\n",
    "    result = llm.invoke(\"Tell me a joke\")\n",
    "    result2 = llm.invoke(\"Tell me a joke\")\n",
    "    print(cb)"
   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bb40375d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
-   "display_name": "poetry-venv-2",
+   "display_name": ".venv",
   "language": "python",
-   "name": "poetry-venv-2"
+   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
@ -353,7 +361,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.11.4"
  }
 },
 "nbformat": 4,
--- a/libs/community/langchain_community/chat_models/bedrock.py
+++ b/libs/community/langchain_community/chat_models/bedrock.py
@ -2,6 +2,7 @@ import re
 from collections import defaultdict
 from typing import Any, Dict, Iterator, List, Optional, Tuple, Union

+from langchain_core._api.deprecation import deprecated
 from langchain_core.callbacks import (
    CallbackManagerForLLMRun,
 )
@ -195,6 +196,9 @@ class ChatPromptAdapter:
 _message_type_lookups = {"human": "user", "ai": "assistant"}


+@deprecated(
+    since="0.0.34", removal="0.3", alternative_import="langchain_aws.ChatBedrock"
+)
 class BedrockChat(BaseChatModel, BedrockBase):
    """Chat model that uses the Bedrock API."""

--- a/libs/community/langchain_community/llms/bedrock.py
+++ b/libs/community/langchain_community/llms/bedrock.py
@ -14,6 +14,7 @@ from typing import (
    Tuple,
 )

+from langchain_core._api.deprecation import deprecated
 from langchain_core.callbacks import (
    AsyncCallbackManagerForLLMRun,
    CallbackManagerForLLMRun,
@ -711,6 +712,9 @@ class BedrockBase(BaseModel, ABC):
                run_manager.on_llm_new_token(chunk.text, chunk=chunk)  # type: ignore[unused-coroutine]


+@deprecated(
+    since="0.0.34", removal="0.3", alternative_import="langchain_aws.BedrockLLM"
+)
 class Bedrock(LLM, BedrockBase):
    """Bedrock models.

--- a/libs/core/langchain_core/load/mapping.py
+++ b/libs/core/langchain_core/load/mapping.py
@ -235,10 +235,10 @@ SERIALIZABLE_MAPPING: Dict[Tuple[str, ...], Tuple[str, ...]] = {
        "AzureChatOpenAI",
    ),
    ("langchain", "chat_models", "bedrock", "BedrockChat"): (
-        "langchain",
+        "langchain_aws",
        "chat_models",
        "bedrock",
-        "BedrockChat",
+        "ChatBedrock",
    ),
    ("langchain", "chat_models", "anthropic", "ChatAnthropic"): (
        "langchain_anthropic",
@ -311,10 +311,10 @@ SERIALIZABLE_MAPPING: Dict[Tuple[str, ...], Tuple[str, ...]] = {
        "BaseOpenAI",
    ),
    ("langchain", "llms", "bedrock", "Bedrock"): (
-        "langchain",
+        "langchain_aws",
        "llms",
        "bedrock",
-        "Bedrock",
+        "BedrockLLM",
    ),
    ("langchain", "llms", "fireworks", "Fireworks"): (
        "langchain",
--- a/templates/bedrock-jcvd/bedrock_jcvd/chain.py
+++ b/templates/bedrock-jcvd/bedrock_jcvd/chain.py
@ -1,6 +1,6 @@
 import os

-from langchain_community.chat_models import BedrockChat
+from langchain_aws import ChatBedrock
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.runnables import ConfigurableField

@ -16,11 +16,11 @@ _model_kwargs = {
 # Full list of base model IDs is available at
 # https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html
 _model_alts = {
-    "claude_2_1": BedrockChat(
+    "claude_2_1": ChatBedrock(
        model_id="anthropic.claude-v2:1", model_kwargs=_model_kwargs
    ),
-    "claude_1": BedrockChat(model_id="anthropic.claude-v1", model_kwargs=_model_kwargs),
-    "claude_instant_1": BedrockChat(
+    "claude_1": ChatBedrock(model_id="anthropic.claude-v1", model_kwargs=_model_kwargs),
+    "claude_instant_1": ChatBedrock(
        model_id="anthropic.claude-instant-v1", model_kwargs=_model_kwargs
    ),
 }
@ -34,7 +34,7 @@ _prompt = ChatPromptTemplate.from_messages(
    ]
 )

-_model = BedrockChat(
+_model = ChatBedrock(
    model_id="anthropic.claude-v2", model_kwargs=_model_kwargs
 ).configurable_alternatives(
    which=ConfigurableField(